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Through a range of carefully chosen scenarios and deliberations around the risks and benefits afforded by data-driven media personalisation technologies and algorithms, we paid close attention to citizens\u2019 voices as our multidisciplinary team sought to engage the public on what \u2018good\u2019 might look like in the context of media personalisation. We paid particular attention to risks and opportunities, examining practical use-cases and scenarios, and our three-wave councils culminated in citizens producing recommendations for practice and policy. In this article, we focus particularly on citizens\u2019 ethical assessment, critique and improvements proposed on media personalisation methods in relation to benefits, fairness, safety, transparency and accountability. Our findings demonstrate that public expectations and trust in data-driven technologies are, fundamentally, conditional, with significant emphasis placed on transparency, inclusiveness and accessibility. Our findings also point to the context dependency of public expectations, which appears more pertinent to citizens, in hard political as opposed to entertainment spaces. Our conclusions are significant for global data-driven media personalisation environments \u2013 in terms of embedding citizens\u2019 focus on transparency and accountability, but equally, also, we argue that strengthening research methodology, innovatively and rigorously to build in citizen voices at the very inception and core of design \u2013 must become a priority in technology development.<\/jats:p>","DOI":"10.1177\/20539517231184892","type":"journal-article","created":{"date-parts":[[2023,8,18]],"date-time":"2023-08-18T03:44:21Z","timestamp":1692330261000},"update-policy":"https:\/\/doi.org\/10.1177\/sage-journals-update-policy","source":"Crossref","is-referenced-by-count":9,"title":["Conditional trust: Citizens\u2019 council on data-driven media personalisation and public expectations of transparency and accountability"],"prefix":"10.1177","volume":"10","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-1776-5221","authenticated-orcid":false,"given":"Yen Nee","family":"Wong","sequence":"first","affiliation":[{"name":"School of Social Policy, Sociology and Social Research (SSPSSR), University of Kent, Canterbury, UK"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-8749-9953","authenticated-orcid":false,"given":"Rhia","family":"Jones","sequence":"additional","affiliation":[{"name":"Research and Development, British Broadcasting Corporation, Salford, UK"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-0100-1817","authenticated-orcid":false,"given":"Ranjana","family":"Das","sequence":"additional","affiliation":[{"name":"Department of Sociology, University of Surrey, Guildford, UK"}]},{"given":"Philip","family":"Jackson","sequence":"additional","affiliation":[{"name":"Institute for People-Centred Artificial Intelligence, University Of Surrey, Guildford, UK"}]}],"member":"179","published-online":{"date-parts":[[2023,8,18]]},"reference":[{"key":"bibr1-20539517231184892","doi-asserted-by":"publisher","DOI":"10.1016\/S0277-9536(02)00343-X"},{"key":"bibr2-20539517231184892","doi-asserted-by":"publisher","DOI":"10.1016\/j.socscimed.2007.01.013"},{"key":"bibr3-20539517231184892","unstructured":"Ada Lovelace Institute (2020) Rapid evidence review. 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